Mike Page

Bio: Mike Page is an academic researcher from University of Hertfordshire. The author has contributed to research in topics: Recall & Short-term memory. The author has an hindex of 24, co-authored 52 publications receiving 2936 citations. Previous affiliations of Mike Page include Cognition and Brain Sciences Unit & Medical Research Council.

The primacy model : A new model of immediate serial recall

Abstract: A new model of immediate serial recall is presented: the primacy model. The primacy model stores order information by means of the assumption that the strength of activation of successive list items decreases across list position to form a primacy gradient. Ordered recall is supported by a repeated cycle of operations involving a noisy choice of the most active item followed by suppression of the chosen item. Word-length and list-length effects are attributed to a decay process that occurs both during input, when effective rehearsal is prevented, and during output. The phonological similarity effect is attributed to a second stage of processing at which phonological confusions occur. The primacy model produces accurate simulations of the effects of word length, list length, and phonological similarity.

Unchained memory: Error patterns rule out chaining models of immediate serial recall.

Abstract: Many models of serial recall assume a chaining mechanism whereby each item associatively evokes the next in sequence Chaining predicts that, when sequences comprise alternating confusable and non-confusable items, confusable items should increase the probability of errors in recall of following non-confusable items Two experiments using visual presentation and one using vocalized presentation test this prediction and demonstrate that: (1) more errors occur in recall of confusable than alternated non-confusable items, revealing a “sawtooth” in serial position curves; (2) the presence of confusable items often has no influence on recall of the non-confusable items; and (3) the confusability of items does not affect the type of errors that follow them These results are inconsistent with the chaining hypothesis Further analysis of errors shows that most transpositions occur over short distances (the locality constraint), confusable items tend to interchange (the similarity constraint), and repeated respon

Connectionist modelling in psychology: A localist manifesto

Abstract: Over the last decade, fully distributed models have become dominant in connectionist psychological modelling, whereas the virtues of localist models have been underestimated. This target article illustrates some of the benefits of localist modelling. Localist models are characterized by the presence of localist representations rather than the absence of distributed representations. A general- ized localist model is proposed that exhibits many of the properties of fully distributed models. It can be applied to a number of prob- lems that are difficult for fully distributed models, and its applicability can be extended through comparisons with a number of classic mathematical models of behaviour. There are reasons why localist models have been underused, though these often misconstrue the lo- calist position. In particular, many conclusions about connectionist representation, based on neuroscientific observation, can be called into question. There are still some problems inherent in the application of fully distributed systems and some inadequacies in proposed solutions to these problems. In the domain of psychological modelling, localist modelling is to be preferred.

A model linking immediate serial recall, the Hebb repetition effect and the learning of phonological word forms.

Abstract: We briefly review the considerable evidence for a common ordering mechanism underlying both immediate serial recall (ISR) tasks (e.g. digit span, non-word repetition) and the learning of phonological word forms. In addition, we discuss how recent work on the Hebb repetition effect is consistent with the idea that learning in this task is itself a laboratory analogue of the sequence-learning component of phonological word-form learning. In this light, we present a unifying modelling framework that seeks to account for ISR and Hebb repetition effects, while being extensible to word-form learning. Because word-form learning is performed in the service of later word recognition, our modelling framework also subsumes a mechanism for word recognition from continuous speech. Simulations of a computational implementation of the modelling framework are presented and are shown to be in accordance with data from the Hebb repetition paradigm.

Sources of Method Bias in Social Science Research and Recommendations on How to Control It

Abstract: Despite the concern that has been expressed about potential method biases, and the pervasiveness of research settings with the potential to produce them, there is disagreement about whether they really are a problem for researchers in the behavioral sciences. Therefore, the purpose of this review is to explore the current state of knowledge about method biases. First, we explore the meaning of the terms “method” and “method bias” and then we examine whether method biases influence all measures equally. Next, we review the evidence of the effects that method biases have on individual measures and on the covariation between different constructs. Following this, we evaluate the procedural and statistical remedies that have been used to control method biases and provide recommendations for minimizing method bias.

Working memory: looking back and looking forward

Abstract: The concept of working memory proposes that a dedicated system maintains and stores information in the short term, and that this system underlies human thought processes. Current views of working memory involve a central executive and two storage systems: the phonological loop and the visuospatial sketchpad. Although this basic model was first proposed 30 years ago, it has continued to develop and to stimulate research and debate. The model and the most recent results are reviewed in this article.

DRC: a dual route cascaded model of visual word recognition and reading aloud.

Abstract: This article describes the Dual Route Cascaded (DRC) model, a computational model of visual word recognition and reading aloud. The DRC is a computational realization of the dual-route theory of reading, and is the only computational model of reading that can perform the 2 tasks most commonly used to study reading: lexical decision and reading aloud. For both tasks, the authors show that a wide variety of variables that influence human latencies influence the DRC model's latencies in exactly the same way. The DRC model simulates a number of such effects that other computational models of reading do not, but there appear to be no effects that any other current computational model of reading can simulate but that the DRC model cannot. The authors conclude that the DRC model is the most successful of the existing computational models of reading.

Working Memory: Theories, Models, and Controversies

Abstract: I present an account of the origins and development of the multicomponent approach to working memory, making a distinction between the overall theoretical framework, which has remained relatively stable, and the attempts to build more specific models within this framework. I follow this with a brief discussion of alternative models and their relationship to the framework. I conclude with speculations on further developments and a comment on the value of attempting to apply models and theories beyond the laboratory studies on which they are typically based.